Your values in csv are non-sensical.

I am not aware of a single function that will read the pts files, but you can 
loop over the list of files and use read.table to read any ascii format. So 
something like this would work for your case

pts.files=dir(patt='pts')
temp=read.table(file=pts.files[1], skip=2, sep=' ', header = F)
LM=array(dim=c(nrow(temp)), 3, length(pts.files))

for (i in 1:length) LM[,,i]=read.table(file=pts.files[i], skip=2, sep=" ", 
header=F)[,2:4]

I didn’t check it, so you may need to edit a few things.
M


From: Pablo Fisichella [mailto:fisichellapa...@gmail.com]
Sent: Friday, July 14, 2017 7:51 AM
To: Antonio Profico <antonio.prof...@uniroma1.it>
Cc: MORPHMET <morphmet@morphometrics.org>; morphmet_modera...@morphometrics.org
Subject: Re: [MORPHMET] Question on Morpho

Dear Antonio

Excuse my delayed response. Thank you, your suggestion work quite fine, I made 
the GPA. However, as Paolo mentioned the coords looks so strange. I made .csv 
files from .pts files (in landmark). Here I attach one of my .csv and the 
corresponding .pts file. There is a way to read multiple .txt files from a 
folder similar to read.csv.folder?. which is the right format of the data 
frame? I have 3D coordinates derived from Amira and microscribe.

Thank you

2017-07-13 5:30 GMT-03:00 Antonio Profico 
<antonio.prof...@uniroma1.it<mailto:antonio.prof...@uniroma1.it>>:
Dear Pablo,

try:  proc <- ProcGPA(a$arr).

The object "a" is a list, the array is an element (arr) of the list.

Let me know if works,

Antonio

2017-07-13 4:59 GMT+01:00 Pablo Fisichella 
<fisichellapa...@gmail.com<mailto:fisichellapa...@gmail.com>>:
Dear All

I am using the package Morpho in order to make some GM analyses but I obtained 
some errors. Now I am trying to use the function read.csv.folder

I ran this command

a<-read.csv.folder("E:/Documents/Zan2", x = 2:44, y = 2:4, rownames = NULL, 
header = TRUE, dec = ",", sep = ";", pattern = "csv", addSpec = NULL, back = 
TRUE)

In the r console appeared my 5 files .csv (see below) with 43 
landmarks/semilandmark in 3 dimensions for 5 individuals (0093, 0137, 0377, 
1865, 1880)

Then I tried perform a Procrustes Analysis using this function: proc <- 
ProcGPA(a) however this error appear: Error in addo(a3) : please provide 3D 
numeric array

I feel that this error is related to my data array but I dont know how I can 
solve this in order to run a GPA

thanks in advance, I appreciate any help you can give me.

cheers,

Pablo

$arr
, , 0093

          X         Y        Z
1  3.30e+08 -1.08e+08 5.22e+08
2  2.94e+08 -5.35e+07 5.12e+08
3  2.76e+08 -7.79e+07 5.59e+08
4  3.13e+08 -1.37e+08 5.48e+08
5  3.21e+08 -1.35e+08 5.45e+08
6  3.27e+08 -1.33e+08 5.42e+08
7  3.32e+08 -1.30e+08 5.39e+08
8  3.36e+08 -1.28e+08 5.36e+08
9  3.38e+08 -1.25e+08 5.34e+08
10 3.39e+08 -1.23e+08 5.32e+08
11 3.39e+08 -1.20e+08 5.30e+08
12 3.37e+08 -1.17e+08 5.29e+08
13 3.33e+08 -1.14e+08 5.27e+08
14 3.29e+08 -9.43e+07 5.21e+08
15 3.30e+08 -9.20e+07 5.19e+08
16 3.31e+08 -8.92e+07 5.17e+08
17 3.31e+08 -8.59e+07 5.16e+08
18 3.30e+08 -8.20e+07 5.15e+08
19 3.28e+08 -7.77e+07 5.14e+08
20 3.24e+08 -7.33e+07 5.13e+08
21 3.19e+08 -6.86e+07 5.11e+08
22 3.12e+08 -6.36e+07 5.10e+08
23 3.04e+08 -5.84e+07 5.08e+08
24 2.84e+08 -4.42e+07 5.20e+08
25 2.81e+08 -4.40e+07 5.27e+08
26 2.79e+08 -4.37e+07 5.32e+08
27 2.78e+08 -4.28e+07 5.38e+08
28 2.77e+08 -4.35e+07 5.43e+08
29 2.76e+08 -4.60e+07 5.47e+08
30 2.76e+08 -4.93e+07 5.50e+08
31 2.75e+08 -5.34e+07 5.53e+08
32 2.76e+08 -5.83e+07 5.55e+08
33 2.76e+08 -6.43e+07 5.56e+08
34 2.83e+08 -8.41e+07 5.67e+08
35 2.85e+08 -8.59e+07 5.69e+08
36 2.87e+08 -8.77e+07 5.70e+08
37 2.89e+08 -8.99e+07 5.72e+08
38 2.91e+08 -9.27e+07 5.73e+08
39 2.93e+08 -9.67e+07 5.74e+08
40 2.96e+08 -1.02e+08 5.74e+08
41 2.97e+08 -1.09e+08 5.73e+08
42 2.97e+08 -1.17e+08 5.69e+08
43 2.96e+08 -1.26e+08 5.65e+08

, , 0137

          X        Y        Z
1  5.31e+08 56600000 1.45e+08
2  5.64e+08 -3300000 1.47e+08
3  5.85e+08 21900000 1.03e+08
4  5.35e+08 73100000 9.86e+07
5  5.35e+08 75800000 1.07e+08
6  5.34e+08 77800000 1.14e+08
7  5.35e+08 79400000 1.20e+08
8  5.34e+08 79900000 1.26e+08
9  5.34e+08 79100000 1.31e+08
10 5.33e+08 77500000 1.35e+08
11 5.33e+08 74900000 1.38e+08
12 5.31e+08 70900000 1.40e+08
13 5.30e+08 66200000 1.41e+08
14 5.39e+08 54700000 1.50e+08
15 5.42e+08 53200000 1.53e+08
16 5.44e+08 51600000 1.55e+08
17 5.47e+08 49400000 1.57e+08
18 5.49e+08 46100000 1.59e+08
19 5.52e+08 41200000 1.61e+08
20 5.54e+08 34000000 1.61e+08
21 5.56e+08 24900000 1.59e+08
22 5.57e+08 14500000 1.57e+08
23 5.58e+08  2910000 1.54e+08
24 5.77e+08 -6540000 1.40e+08
25 5.82e+08 -3350000 1.34e+08
26 5.88e+08   632000 1.31e+08
27 5.92e+08  4170000 1.27e+08
28 5.94e+08  6870000 1.23e+08
29 5.95e+08  9310000 1.19e+08
30 5.94e+08 11500000 1.16e+08
31 5.93e+08 13400000 1.13e+08
32 5.92e+08 15300000 1.11e+08
33 5.90e+08 17300000 1.09e+08
34 5.85e+08 32800000 9.65e+07
35 5.85e+08 36100000 9.61e+07
36 5.84e+08 39300000 9.58e+07
37 5.84e+08 42700000 9.54e+07
38 5.83e+08 46500000 9.45e+07
39 5.81e+08 50400000 9.30e+07
40 5.76e+08 54200000 9.10e+07
41 5.70e+08 58300000 8.85e+07
42 5.62e+08 60800000 8.60e+07
43 5.52e+08 63100000 8.31e+07

, , 0377

          X        Y        Z
1  5.48e+08 74100000 1.08e+08
2  5.79e+08 14000000 1.01e+08
3  6.04e+08 47100000 5.61e+07
4  5.56e+08 97700000 5.76e+07
5  5.57e+08 98500000 6.97e+07
6  5.56e+08 97400000 8.03e+07
7  5.55e+08 96300000 8.91e+07
8  5.54e+08 94400000 9.59e+07
9  5.52e+08 91900000 1.01e+08
10 5.50e+08 88500000 1.03e+08
11 5.49e+08 85800000 1.04e+08
12 5.49e+08 83500000 1.04e+08
13 5.49e+08 80600000 1.04e+08
14 5.56e+08 68300000 1.14e+08
15 5.58e+08 66000000 1.16e+08
16 5.60e+08 63600000 1.17e+08
17 5.63e+08 61200000 1.19e+08
18 5.66e+08 58200000 1.21e+08
19 5.69e+08 54100000 1.22e+08
20 5.71e+08 48000000 1.22e+08
21 5.72e+08 39600000 1.20e+08
22 5.73e+08 29600000 1.19e+08
23 5.71e+08 20000000 1.13e+08
24 5.93e+08 11100000 9.49e+07
25 5.99e+08 13800000 9.20e+07
26 6.04e+08 16500000 8.87e+07
27 6.08e+08 19300000 8.54e+07
28 6.11e+08 22300000 8.19e+07
29 6.13e+08 25300000 7.83e+07
30 6.14e+08 28300000 7.44e+07
31 6.13e+08 31400000 7.05e+07
32 6.12e+08 34600000 6.64e+07
33 6.10e+08 38100000 6.21e+07
34 6.05e+08 59700000 5.27e+07
35 6.05e+08 63900000 5.30e+07
36 6.04e+08 67800000 5.28e+07
37 6.02e+08 71500000 5.25e+07
38 6.01e+08 75300000 5.22e+07
39 5.99e+08 79300000 5.19e+07
40 5.96e+08 83500000 5.13e+07
41 5.91e+08 87200000 4.98e+07
42 5.84e+08 88800000 4.73e+07
43 5.77e+08 90300000 4.48e+07

, , 1865

          X         Y        Z
1  4.06e+08 -3.58e+08 5.56e+08
2  3.76e+08 -2.90e+08 5.60e+08
3  3.62e+08 -3.32e+08 5.99e+08
4  3.84e+08 -3.85e+08 5.76e+08
5  3.89e+08 -3.84e+08 5.74e+08
6  3.93e+08 -3.83e+08 5.73e+08
7  3.98e+08 -3.81e+08 5.72e+08
8  4.01e+08 -3.79e+08 5.70e+08
9  4.03e+08 -3.77e+08 5.68e+08
10 4.05e+08 -3.74e+08 5.67e+08
11 4.07e+08 -3.71e+08 5.65e+08
12 4.08e+08 -3.68e+08 5.63e+08
13 4.08e+08 -3.64e+08 5.61e+08
14 4.07e+08 -3.45e+08 5.55e+08
15 4.09e+08 -3.40e+08 5.54e+08
16 4.11e+08 -3.36e+08 5.54e+08
17 4.11e+08 -3.31e+08 5.53e+08
18 4.10e+08 -3.26e+08 5.53e+08
19 4.08e+08 -3.21e+08 5.52e+08
20 4.02e+08 -3.16e+08 5.51e+08
21 3.97e+08 -3.10e+08 5.51e+08
22 3.92e+08 -3.02e+08 5.51e+08
23 3.85e+08 -2.94e+08 5.51e+08
24 3.68e+08 -2.87e+08 5.71e+08
25 3.67e+08 -2.88e+08 5.76e+08
26 3.67e+08 -2.88e+08 5.81e+08
27 3.66e+08 -2.90e+08 5.85e+08
28 3.64e+08 -2.94e+08 5.88e+08
29 3.63e+08 -2.98e+08 5.90e+08
30 3.61e+08 -3.02e+08 5.93e+08
31 3.59e+08 -3.07e+08 5.95e+08
32 3.57e+08 -3.13e+08 5.95e+08
33 3.56e+08 -3.20e+08 5.95e+08
34 3.66e+08 -3.40e+08 6.04e+08
35 3.68e+08 -3.42e+08 6.05e+08
36 3.69e+08 -3.45e+08 6.06e+08
37 3.69e+08 -3.48e+08 6.06e+08
38 3.70e+08 -3.52e+08 6.06e+08
39 3.70e+08 -3.56e+08 6.05e+08
40 3.71e+08 -3.61e+08 6.04e+08
41 3.70e+08 -3.66e+08 6.02e+08
42 3.69e+08 -3.71e+08 5.99e+08
43 3.67e+08 -3.77e+08 5.94e+08

, , 1880

          X         Y        Z
1  3.49e+08 -1.07e+08 6.05e+08
2  3.17e+08 -2.81e+07 6.07e+08
3  3.00e+08 -6.88e+07 6.51e+08
4  3.22e+08 -1.39e+08 6.27e+08
5  3.30e+08 -1.36e+08 6.23e+08
6  3.37e+08 -1.34e+08 6.20e+08
7  3.42e+08 -1.32e+08 6.17e+08
8  3.47e+08 -1.30e+08 6.15e+08
9  3.50e+08 -1.27e+08 6.14e+08
10 3.52e+08 -1.24e+08 6.12e+08
11 3.53e+08 -1.21e+08 6.11e+08
12 3.53e+08 -1.19e+08 6.11e+08
13 3.52e+08 -1.15e+08 6.11e+08
14 3.50e+08 -9.35e+07 6.04e+08
15 3.53e+08 -8.75e+07 6.03e+08
16 3.54e+08 -8.14e+07 6.01e+08
17 3.55e+08 -7.53e+07 6.01e+08
18 3.54e+08 -6.91e+07 6.00e+08
19 3.53e+08 -6.26e+07 6.00e+08
20 3.50e+08 -5.61e+07 5.99e+08
21 3.44e+08 -4.97e+07 5.98e+08
22 3.38e+08 -4.26e+07 5.98e+08
23 3.30e+08 -3.65e+07 5.97e+08
24 3.11e+08 -2.72e+07 6.21e+08
25 3.09e+08 -3.05e+07 6.27e+08
26 3.09e+08 -3.28e+07 6.33e+08
27 3.09e+08 -3.43e+07 6.39e+08
28 3.09e+08 -3.73e+07 6.44e+08
29 3.07e+08 -4.08e+07 6.47e+08
30 3.06e+08 -4.44e+07 6.49e+08
31 3.05e+08 -4.82e+07 6.50e+08
32 3.04e+08 -5.23e+07 6.51e+08
33 3.03e+08 -5.67e+07 6.51e+08
34 3.04e+08 -7.65e+07 6.56e+08
35 3.05e+08 -8.11e+07 6.58e+08
36 3.06e+08 -8.54e+07 6.60e+08
37 3.07e+08 -8.99e+07 6.61e+08
38 3.08e+08 -9.48e+07 6.62e+08
39 3.09e+08 -1.00e+08 6.62e+08
40 3.10e+08 -1.07e+08 6.60e+08
41 3.08e+08 -1.13e+08 6.56e+08
42 3.06e+08 -1.20e+08 6.48e+08
43 3.05e+08 -1.28e+08 6.43e+08


$NAs
NULL

$NA.list
NULL

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Antonio Profico
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Department of Environmental Biology – Dipartimento di Biologia Ambientale
SAPIENZA Università di Roma

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